An important problem in generative models is to generate fair distributions w.r.t a set of attributes of interest.
For instance, Figure REF (a) shows that StyleGAN2 generates images with bias across races and ages. PromptGen de-biases StyleGAN2 models trained on FFHQ 1024\(^2\)  and MetFaces 1024\(^2\)  [1]} in terms of categorical attributes, using the moment constraint defined in Eq. (REF ) and Eq. (REF ). As control, we used a classifier trained on FairFace 224\(^2\)  [2]} as \(\mathbf {\gamma }\) .
We defined \(\mathbf {\mu }= \big (|\mathcal {A}|^{-1}, \ldots , |\mathcal {A}|^{-1}\big )\) , where \(\mathcal {A}\)  is the set of races.
Similar to the energy weights \(\lambda _i\)  defined in Eq. (REF ), we propose to rescale the trained \(\hat{\mathbf {\beta }}\)  as \(\lambda \hat{\mathbf {\beta }}\) .
Figure REF  shows that PromptGen de-biases the race and age effectively.
